Package: data4health 0.1.1

Daniela Lührsen

data4health: A Practical Workflow for Health Data Wrangling

Provides a streamlined workflow for cleaning, transforming, filtering, aggregating, and exporting epidemiological line list data. The package is designed for public health surveillance and clinical datasets where each row represents an individual case. It supports common data-wrangling tasks and multi-format data import/export (e.g., 'csv', 'rds', 'xlsx', 'json', 'dbf'). The functions are designed to be combined into a clear and reproducible pipeline while remaining flexible enough for use in standalone data-processing steps. 'data4health' is part of the '4health' toolkit, which integrates health, climate, land-use, and socioeconomic data workflows. More information on the '4health' tools can be found on the HARMONIZE website <https://harmonize-tools.org/toolkits>.

Authors:Daniela Lührsen [aut, cre], Carles Milà [aut], Raquel Lana [aut], Rachel Lowe [aut], Mark Adler [cph], Daniela Petruzalek [cph]

data4health_0.1.1.tar.gz
data4health_0.1.1.tar.gz(r-4.7-arm64)data4health_0.1.1.tar.gz(r-4.7-x86_64)data4health_0.1.1.tar.gz(r-4.6-arm64)data4health_0.1.1.tar.gz(r-4.6-x86_64)
data4health_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
data4health/json (API)

# Install 'data4health' in R:
install.packages('data4health', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/bsc-es/ghrtools/issues

Datasets:

On CRAN:

Conda:

3.00 score 7 exports 84 dependencies

Last updated from:1934dd890e. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK165
linux-devel-x86_64OK174
source / vignettesOK257
linux-release-arm64OK159
linux-release-x86_64OK178
wasm-releaseOK149

Exports:d4h_aggregated4h_cleand4h_exampled4h_filterd4h_loadd4h_saved4h_ui

Dependencies:askpassbase64encbslibcachemcellrangerclicolorspacecommonmarkcowplotcpp11crayoncrosstalkcurldata.tabledigestdplyrevaluatefarverfastmapfontawesomeforeignfsgenericsggplot2GHRexploregluegtablehighrhmshtmltoolshtmlwidgetshttpuvhttrisobandjquerylibjsonliteknitrlabelinglaterlazyevallifecyclelubridatemagrittrmemoisemimeopensslotelpillarpkgconfigplotlyprettyunitsprogresspromisespurrrR6rappdirsRColorBrewerRcppreadxlrematchrlangrmarkdownS7sassscalesshinyshinyAcesourcetoolsstringistringrsystibbletidyrtidyselecttimechangetinytexutf8vctrsviridisLitewithrwritexlxfunxtableyaml

Getting Started with data4health: A Practical Workflow for Health Data Wrangling
Overview | Who is this vignette for? | Data requirements | The data4health workflow | 1. Loading data with d4h_load() | 2. Cleaning data with d4h_clean() | 3. Filtering data with d4h_filter() | 4. Aggregating data with d4h_aggregate() | 5. Saving results with d4h_save() | Putting it all together
Rendered fromdata4health_overview.Rmdusingknitr::rmarkdown

Last update: 2026-07-07
Started: 2026-07-07

How to access Health Data
Rendered fromaccess_health_data.Rmdusingknitr::rmarkdown

Last update: 2026-07-07
Started: 2026-07-07